IR-YOLO: Real-Time Infrared Vehicle and Pedestrian Detection

Road traffic safety can decrease when drivers drive in a low-visibility environment.The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents.To tackle the challenges posed by the low recognition accuracy and the substan-tial computational burden associated with current infrared pedestrian-vehicle detection methods,an infrared pedestrian-vehicle detection method A proposal is presented,based on an enhanced version of You Only Look Once version 5(YOLOv5).First,A head specifically designed for detecting small targets has been integrated into the model to make full use of shallow feature information to enhance the accuracy in detecting small targets.Second,the Focal Generalized Intersection over Union(GIoU)is employed as an alternative to the original loss function to address issues related to target overlap and category imbalance.Third,the distribution shift convolution optimization feature extraction operator is used to alleviate the computational burden of the model without significantly compromising detection accuracy.The test results of the improved algorithm show that its average accuracy(mAP)reaches 90.1%.Specifically,the Giga Floating Point Operations Per second(GFLOPs)of the improved algorithm is only 9.1.In contrast,the improved algorithms outperformed the other algorithms on similar GFLOPs,such as YOLOv6n(11.9),YOLOv8n(8.7),YOLOv7t(13.2)and YOLOv5s(16.0).The mAPs that are 4.4%,3%,3.5%,and 1.7%greater than those of these algorithms show that the improved algorithm achieves higher accuracy in target detection tasks under similar computational resource overhead.On the other hand,compared with other algorithms such as YOLOv8l(91.1%),YOLOv6l(89.5%),YOLOv7(90.8%),and YOLOv3(90.1%),the improved algorithm needs only 5.5%,2.3%,8.6%,and 2.3%,respectively,of the GFLOPs.The improved algorithm has shown significant advancements in balancing accuracy and computational efficiency,making it promising for practical use in resource-limited scenarios.

Report for Type 2 Bayes-Fuzzy Estimation in No-Data Problem

It is well known that the system (1 + 1) can be unequal to 2, because this system has both observation error and system error. Furthermore, we must provide our mustered service within our cool head and warm heart, where two states of nature are existing upon us. Any system is regarded as the two-dimensional variable error model. On the other hand, we consider that the fuzziness is existing in this system. Though we can usually obtain the fuzzy number from the possibility theory, it is not fuzzy but possibility, because the possibility function is as same as the likelihood function, and we can obtain the possibility measure by the maximal likelihood method (i.e. max product method proposed by Dr. Hideo Tanaka). Therefore, Fuzzy is regarded as the only one case according to Vague, which has both some state of nature in this world and another state of nature in the other world. Here, we can consider that Type 1 Vague Event in other world can be obtained by mapping and translating from Type 1 fuzzy Event in this world. We named this estimation as Type 1 Bayes-Fuzzy Estimation. When the Vague Events were abnormal (ex. under War), we need to consider that another world could exist around other world. In this case, we call it Type 2 Bayes-Fuzzy Estimation. Where Hori et al. constructed the stochastic different equation upon Type 1 Vague Events, along with the general following probabilistic introduction method from the single regression model, multi-regression model, AR model, Markov (decision) process, to the stochastic different equation. Furthermore, we showed that the system theory approach is Possibility Markov Process, and that the making decision approach is Sequential Bayes Estimation, too. After all, Type 1 Bays-Fuzzy estimation is the special case in Bayes estimation, because the pareto solutions can exist in two stochastic different equations upon Type 2 Vague Events, after we ignore one equation each other (note that this is Type 1 case), we can obtain both its system solution and its decision solution. Here, it is noted that Type 2 Vague estimation can be applied to the shallow abnormal decision problem with possibility reserved judgement. However, it is very important problem that we can have no idea for possibility reserved judgement under the deepest abnormal envelopment (ex. under War). Expect for this deepest abnormal decision problem, Bayes estimation can completely cover fuzzy estimation. In this paper, we explain our flowing study and further research object forward to this deepest abnormal decision problem.

Data-driven polarimetric imaging: a review

This study reviews the recent advances in data-driven polarimetric imaging technologies based on a wide range of practical applications.The widespread international research and activity in polarimetric imaging techniques demonstrate their broad applications and interest.Polarization information is increasingly incorporated into convolutional neural networks(CNN)as a supplemental feature of objects to improve performance in computer vision task applications.Polarimetric imaging and deep learning can extract abundant information to address various challenges.Therefore,this article briefly reviews recent developments in data-driven polarimetric imaging,including polarimetric descattering,3D imaging,reflection removal,target detection,and biomedical imaging.Furthermore,we synthetically analyze the input,datasets,and loss functions and list the existing datasets and loss functions with an evaluation of their advantages and disadvantages.We also highlight the significance of data-driven polarimetric imaging in future research and development.

Development of a Musical-based Interaction System for the Waseda Flutist Robot-Implementation of a Real-time Vision Interface Based on the Particle Filter Algorithm

The aim of this paper is to create an interface for human-robot interaction.Specifically,musical performance parameters(i.e.vibrato expression)of the Waseda Flutist Robot No.4 Refined IV(WF-4RIV)are to be manipulated.This research focused on enabling the WF-4RIV to interact with human players(musicians)in a natural way.In this paper,as the first approach,a vision processing algorithm,which is able to track the 3D-orientation and position of a musical instrument,was developed.In particular,the robot acquires image data through two cameras attached to its head.Using color histogram matching and a particle filter,the position of the musician's hands on the instrument are tracked.Analysis of this data determines orientation and location of the instrument.These parameters are mapped to manipulate the musical expression of the WF-4RIV,more specifically sound vibrato and volume values.The authors present preliminary experiments to determine if the robot may dynamically change musical parameters while interacting with a human player(i.e.vibrato etc.).From the experimental results,they may confirm the feasibility of the interaction during the performance,although further research must be carried out to consider the physical constraints of the flutist robot.

Synthesis of crystal-phase and color tunable mixed anion co-doped titanium oxides and their controllable photocatalytic activity

B and N mixed anions co-doped titania with various crystal phases such as anatase,brookite,and rutile were successfully synthesized by a hydrothermal synthesis followed by heat treatment in an ammonia gas atmosphere at 550-650℃(denoted as BN-Ana_x,BN-Bro_x,and BN-Rut_x,x is the treatment temperature).The colors of as-prepared BN-Ana,BN-Bro,and BN-Rut are red,yellow-green,and cyangreen,respectively.The color changing mechanism of titania was related to their various band gap structure and the existence of B-N bonding.The nitridation temperature exhibits effective color changing compared to that of nitridation time.The different phases of the mixed anion codoped titania possess different photocatalytic deNO_(x) activity.The BN-Ana and BN-Rut show poor photocatalytic deNO_(x) activity,while the BN-Bro shows excellent photocatalytic deNO_(x) activity,better than that of standard titania photocatalyst Degussa P25.The colorful titania with low-photocatalytic activity is heavy metal elements free,indicating their possible applications as nontoxic color pigments or novel cosmetic raw materials.

Guest Editorial: Special issue on machine learning and deep learning algorithms for complex networks

In the latest years,researchers from the industry and academia extensively applied machine learning algorithms in a broad range of domains.The goal of this special issue is to illustrate the most recent applications of deep learning methods in a range of real-life domains and to show the practical utility of these techniques.A particular attention goes towards methods to process network data that is capable of modelling complex artificial and natural systems as the interactions of a multitude of simpler entities.

Identification of microbial metabolites that accelerate the ubiquitindependent degradation of c-Myc

Myc belongs to a family of proto-oncogenes that encode transcription factors.The overexpression of c-Myc causes many types of cancers.Recently,we established a system for screening c-Myc inhibitors and identified antimycin A by screening the RIKEN NPDepo chemical library.The specific mechanism of promoting tumor cell metastasis by high c-Myc expression remains to be explained.In this study,we screened approximately 5,600 microbial extracts using this system and identified a broth prepared from Streptomyces sp.RK19-A0402 strongly inhibits c-Myc transcriptional activity.After purification of the hit broth,we identified compounds closely related to the aglycone of cytovaricin and had a structure similar to that of oligomycin A.Similar to oligomycin A,the hit compounds inhibited mitochondrial complex V.The mitochondria dysfunction caused by the compounds induced the production of reactive oxygen species(ROS),and the ROS activated GSK3α/βthat phosphorylated c-Myc for ubiquitination.This study provides a successful screening strategy for identifying natural products as potential c-Myc inhibitors as potential anticancer agents.

Bio-Inspired Optimal Dispatching of Wind Power Consumption Considering Multi-Time Scale Demand Response and High-Energy Load Participation

Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this paper constructs a bio-inspired computer model.It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load.First,the principle of wind power obstruction with the involvement of a high-energy load is examined in this work.In this step,highenergy load model with different regulation characteristics is established.Then,considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed,a multi-time scale model of coordination optimization is built.An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs,as well as to find the most optimal energy configurationwithin the system.Lastly,we take an example of regional power grid in Gansu Province for simulation analysis.Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system’s operational cost.

Uniquely Decomposable Constellation Group-Based Sparse Vector Coding for Short Packet Communications

Sparse vector coding(SVC)is emerging as a potential technology for short packet communications.To further improve the block error rate(BLER)performance,a uniquely decomposable constellation group-based SVC(UDCG-SVC)is proposed in this article.Additionally,in order to achieve an optimal BLER performance of UDCG-SVC,a problem to optimize the coding gain of UDCG-based superimposed constellation is formulated.Given the energy of rotation constellations in UDCG,this problem is solved by converting it into finding the maximized minimum Euclidean distance of the superimposed constellation.Simulation results demonstrate the validness of our derivation.We also find that the proposed UDCGSVC has better BLER performance compared to other SVC schemes,especially under the high order modulation scenarios.

Ketone bodies and inflammation modulation:A mini-review on ketogenic diet’s potential mechanisms in mood disorders

Mental disorders such as depression and anxiety inflict significant burdens on individuals and society.Commonly prescribed treatments often involve cognitive therapy and medications.However,for patients resistant to these conventional methods,alternative therapies like the Ketogenic Diet(KD)offer a promising avenue.KD and its key metabolite,β-hydroxybutyrate(BHB),have been hypothesized to alleviate mental disorders through antiinflammatory actions,a crucial pathway in the pathophysiology of depression.This mini-review examines 15 clinical trials exploring the influence of KD and BHB on inflammation and their potential roles in managing mental disorders.Both human and animal studies were scrutinized to elucidate possible cellular and molecular mechanisms.Out of the 15 trials,10 reported reduced levels of at least one inflammatory mediator or mRNA post KD or BHB treatment,while two observed an elevation in anti-inflammatory agents.These findings suggest that KD and BHB could modulate cellular inflammatory pathways,highlighting their potential for therapeutic application in mental disorders.

Exercise therapy for sarcopenia and diabetes

Aging is characterized by the gradual deterioration of function at the molecular,cellular,tissue,and organism levels in humans.The typical diseases caused by changes in body composition,as well as functional decline in the human body’s organs due to aging include sarcopenia and metabolic disorders.The accumulation of dysfunctional agingβcells with age can cause decreased glucose tolerance and diabetes.Muscle decline has a multifactorial origin,involving lifestyle habits,disease triggers,and age-dependent biological changes.The reduced function ofβcells in elderly people lowers insulin sensitivity,which affects protein synthesis and interferes with muscle synthesis.The functional decrease and aggravation of disease in elderly people with less regular exercise or physical activity causes imbalances in food intake and a continuous,vicious cycle.In contrast,resistance exercise increases the function ofβcells and protein synthesis in elderly people.In this review,we discuss regular physical activities or exercises to prevent and improve health,which is sarcopenia as decreased muscle mass and metabolic disorders as diabetes in the elderly.

A fuzzy control and neural network based rotor speed controller for maximum power point tracking in permanent magnet synchronous wind power generation system

When the wind speed changes significantly in a permanent magnet synchronous wind power generation system,the maximum power point cannot be easily determined in a timely manner.This study proposes a maximum power reference signal search method based on fuzzy control,which is an improvement to the climbing search method.A neural network-based parameter regulator is proposed to address external wind speed fluctuations,where the parameters of a proportional-integral controller is adjusted to accurately monitor the maximum power point under different wind speed conditions.Finally,the effectiveness of this method is verified via Simulink simulation.

Cobalt phthalocyanine-based conjugated polymer as efficient and exclusive electrocatalyst for CO_(2) reduction to ethanol

Electrocatalytic conversion of carbon dioxide to high value-added chemicals is a promising method for solving the energy crisis and global warming.Electrochemical active metal-containing conjugated polymers have been widely studied for heterogeneous carbon dioxide reduction.In the present contribution,we designed and synthesized a stable cobalt phthalocyanine-based conjugated polymer,named CoPPc-TFPPy-CP,and also explored its electro-catalytic application in carbon dioxide reduction to liquid products in an aqueous solution.In the catalyst,cobalt phthalocyanine acts as building blocks connected with 1,3,6,8-tetrakis(4-formyl phenyl)pyrenes via imine-linkages,leading to mesoporous formation polymers with the pore size centered at 4.1nm.And the central co-balt atoms shifted to a higher oxidation state after condensation.With these chemical and structural natures,the catalyst displayed a remarkable electrocatalytic CO_(2) reduction performance with an ethanol Faradaic efficiency of 43.25%at-1.0V vs RHE.While at the same time,the electrochemical reduction process catalyzed by cobalt phthalocyanine produced only carbon monoxide and hydrogen.To the best of our knowledge,CoPPc-TFPPy-CP is the first example among organic polymers and metal-organic frameworks that produces ethanol from CO_(2) with a remarkable selectivity.

固体气泡探测器-固体核径迹探测器的新类别

利用高能重离子p、He、C、Si、Ar、Fe、Kr和Xe对固体气泡探测器的性质进行了研究。结果表明,固体气泡探测器具有许多与固体核径迹探测器相似的性质,且具有显影主动性、实时记录性、体径迹显示能力等多方面普通固体核径迹探测器所不具有的性能。可以得出结论:固体气泡探测器是固体核径迹探测器的一种新类别。

固体气泡损伤探测器阈起源的实验判别

用 5 0 0MeV/u56Fe,6 5 0MeV/u40Ar ,6 0 0MeV/u2 8Si和 180MeV/u4He对固体气泡损伤探测器 (T- 12型 )进行了实验研究 ,实验结果表明 ,固体气泡损伤探测器的阈特性可用临界能量损失率表征。在一般条件下 ,限定能量损失率在不同重离子产生径迹时不具有相同临界值 ,因此 。

空间乳胶室探测器的研制

"实践八号"乳胶室探测器是我国首次用于空间观测高能电子及伽玛射线的乳胶室探测器.介绍"实践八号"乳胶室探测器的设计原理、数据分析方法、设计过程和初步观测结果等."实践八号"乳胶室探测器空间观测时间为15天,可探测的粒子能量范围为100 GeV～5 TeV.

Cell sheet technology for regeneration of esophageal mucosa

The progress of tissue-engineering technology has realized development of new therapies to treat various disorders by using cultured cells. Cell-and tissue-based therapies have been successfully applied to human patients, and several tissue-engineered products have been approved by the regulatory agencies and are commercially available. In the review article, we describe our experience of development and clinical application of cell sheet-based regenerative medicine.Endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD) have been shown to be useful for removal of gastrointestinal neoplasms with less invasiveness compared with open surgery, especially in esophageal surgery. However, postoperative inflammation and stenosis are major complications observed after intensive mucosal resection. Therefore, we have developed novel regenerative medicine to prevent such complications and promote wound healing of esophageal mucosa after EMR or ESD. Transplantable oral mucosal epithelial cell sheets were fabricated from patients' own oral mucosa. Immediately after EMR or ESD, fabricated autologous cell sheets were endoscopically transplanted to the ulcer sites. We performed a preclinical study with a canine model. In human clinical settings, cell culture and cell sheet fabrication were performed in clean rooms according to good manufacturing practice guidelines, and pharmaceutical drugs were used as supplements to culture medium in place of research regents used in animal study. We believe that cell-based regenerative medicine would be useful to improve quality of life of patients after EMR or ESD.

Energy-Efficient Architecture and Technologies for Device to Device(D2D) Based Proximity Service

Considering that modern mobile terminals possess the capability to detect users' proximity,and offer means to directly communicate and share content with the people in close area,Device-to-Device(D2D) based Proximity Services(ProSe) have recently witnessed great development,which enable users to seek for and utilize relevant value in their physical proximity,and are capable to create numerous new mobile service opportunities.However,without a breakthrough in battery technology,the energy will be the biggest limitation for ProSe.Through incorporating the features of ProSe(D2D communication technologies,abundant built-in sensors,localization-dependent,and context-aware,etc.),this paper thoroughly investigates the energy-efficient architecture and technologies for ProSe from the following four aspects:underlying networking technology,localization,application and architecture features,context-aware and user interactions.Besides exploring specific energy-efficient schemes pertaining to each aspect,this paper offers a perspective for research and applications.In brief,through classifying,summarizing and optimizing the multiple efforts on studying,modeling and reducing energy consumption for ProSe on mobile devices,the paper would provide guide for developers to build energy-efficient ProSe.

GLOBAL STABILITY OF SIRS EPIDEMIC MODELS WITH A CLASS OF NONLINEAR INCIDENCE RATES AND DISTRIBUTED DELAYS

In this article, we establish the global asymptotic stability of a disease-free equilibrium and an endemic equilibrium of an SIRS epidemic model with a class of nonlin- ear incidence rates and distributed delays. By using strict monotonicity of the incidence function and constructing a Lyapunov functional, we obtain sufficient conditions under which the endemic equilibrium is globally asymptotically stable. When the nonlinear inci- dence rate is a saturated incidence rate, our result provides a new global stability condition for a small rate of immunity loss.